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Course Criteria
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3.00 Credits
(Prereq: Grade of C or better in MATH A108, placement higher than MATH A108 or consent of department) Introduction to systematic computer problem-solving using a procedural language. Emphasis is placed upon algorithm development and program implementation. This course also provides exposure to applications such as spreadsheets, database management, and web-page design leading to an advanced level of competency. The course is intended for students who are already familiar with the basic use of computers for non-calculating purposes (word processing, use of the internet, email, etc.) and who desire a background in computer solutions to practical problems.
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3.00 Credits
(Prereq: Placement above MATH A104, or MATH A104 with a grade C or better, or consent of department) This course is designed to help students with no prior exposure to computer science or programming learn to think computationally and write programs to solve real-life problems. The course focuses on problem analysis and the development of algorithms and computer programs in a modern high-level language. This course is for students who want to pursue a major in computer science.
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4.00 Credits
(Prereq: For all applied computer science majors, CSCI A125 with a grade of C or better is the prerequisite for CSCI A145. For all other majors, a grade of C or better in MATH A111 is the prerequisite for CSCI A145.). This is the first course in the two-semester programming course sequence for students majoring in computer science. It teaches program design, coding, debugging, testing, and documentation using good programming style in Java, and provides a foundation for further studies in computer science. Three hours of lectures and three hours of laboratory per week.
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4.00 Credits
(Prereq: Grade of C or higher in CSCI A145) A continuation of CSCI A145. Rigorous development of algorithms and computer programs; elementary data structures. Three hours of lectures and three hours of laboratory per week.
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4.00 Credits
(Prereq: CSCI A125 with a grade of C or better) This course introduces the basics of Data Science. It also teaches additional topics such as inheritance and polymorphism, files, and exception handling. It introduces standard Python libraries for Data Science.
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3.00 Credits
(Prereq: MATH A108 or MATH A108L with a grade or C or better, or placement higher than MATH A108 or MATH A108L, or consent of the department). This course introduces systematic computer problem-solving using a procedural language. Emphasis is placed upon algorithm development and program implementation. This course is intended for students to learn computer visual programming. Emphasis is on the fundamentals of structured design, development, testing, implementation, and documentation. Course topics include language syntax, data and file structures, input/output devices, and files. This course also provides exposure to applications such as spreadsheets, database management, and web-page design leading to an advanced level of competency.
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3.00 Credits
(Prereq: consent of instructor) Programming and application development using selected programming languages. Course content varies and will be announced in the schedule of classes by suffix and title.
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3.00 Credits
(Prereq: CSCI A145 with a grade of C or better) This course covers computer organization and architecture, with a focus on how the various components of computer systems fit together and interact. The goal of this course is to obtain a working knowledge of the lower levels of abstraction of a computer system. Students will learn how to program at both the assembly level and the instruction set architecture level, and obtain an in-depth understanding of how computers work by considering the design of the levels of abstraction and the relationship between the levels.
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3.00 Credits
Covers the impact of computer use on society, the ethical use of software, and the protection of intellectual property rights. The responsibility of professionals will be discussed in the context of the IEEE/ACM professional code of ethics.
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3.00 Credits
(Prereq: Grade of C or better in MATH A174 and CSCI A146, or consent of instructor.) Theory and advanced techniques for representation of information. Abstract data types: lists, stacks, queues, sets, trees, and graphs. Algorithms for sorting, searching, and hashing.
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